计算机科学课程

course description

The Computer Science Intermediate Track provides a unique combination of coding boot camp, and lab touring experiences, as well as UCLA coursework covering critical concepts and skills in computer programming related to statistical inference, in conjunction with hands-on analysis of real-world datasets, including economic data, health data, geographical data, and social networks.

 

The fundamental question this course aims to address is how does one analyze real-world data so as to understand the corresponding phenomenon.  Planned topics include machine learning, data analytics, and statistical modeling classically employed for prediction. The program will be a blend of theoretical and practical instruction, providing a comprehensive, hands-on overview of the Data Science domain.

 

Hands-on projects will form the bulk of the work for the class and will seek to teach students the data science lifecycle: data selection and cleaning, feature engineering, model selection, and prediction methodologies.

 

课程介绍

计算机科学课程为学生提供一个结合编码训练营和实验室参观体验的机会，让学生了解与统计推断有关的计算机编程关键概念和技能，掌握对真实数据进行实际分析，包括经济数据、健康数据、地理数据和社交网络相关数据。

 

本课程旨在解决如何分析真实数据的根本问题。主题包括机器学习、数据分析和用于预测的经典统计模型。该课程将结合理论和实践教学，为学生提供数据科学领域的全面的实践概述。

 

本课程大部分的内容包括实践项目，旨在教授学生数据科学生命周期：数据选择和清理、特征工程、模型选择和预测方法。

课程时间：7月11日--7月29日

入学资格：

- 编程技术背景

- 在线申请

- 托福80以上（Duolinguo 105)

- 申请开放日：2月15日